Genetic design automation: engineering fantasy or scientific renewal?

Abstract

The aim of synthetic biology is to make genetic systems more amenable to engineering, which has naturally led to the development of computer-aided design (CAD) tools. Experimentalists still primarily rely on project-specific ad hoc workflows instead of domain-specific tools, which suggests that CAD tools are lagging behind the front line of the field. Here, we discuss the scientific hurdles that have limited the productivity gains anticipated from existing tools. We argue that the real value of efforts to develop CAD tools is the formalization of genetic design rules that determine the complex relationships between genotype and phenotype.

Figure 1

GDA design flow. Synthetic biology projects typically rely on iterative workflows composed of different tasks. Emerging GDA tool chains rely on numerous software applications that support different phases of the project workflow. The development of a genetic switch [72] will start by expressing the design objective as a list of quantitative requirements: input toggle thresholds, noise margins, switching response time, etc. Once the objective is specified, it is possible to develop a list of genetic parts useable for the project. The choice of biological parts will involve factors such as use of the parts in prior projects, quality of the data characterizing the parts function, or intellectual property considerations. The formalization of design rules often takes place in parallel to the parts library development. Design rules may express rules such as whether it is acceptable to have polycistronic expression cassettes or if the design should be split between different plasmids. Only after parts have been selected and a strategy has been agreed upon is it possible to start designing constructs. In the fabrication phase, the construct is assembled usually by combining de novo gene synthesis and cloning of existing DNA sequences. Users use molecular biology software suites to facilitate assembly or order the sequence from a gene synthesis company. Experimentalists insert the synthetic DNA molecule into the host of choice and collect phenotypic data. Experimental data is then processed, for example by reducing microscopy images into time series of quantitative data. Performance is evaluated by considering simulations, experimental data, and the original specifications. At nearly every stage, software interacts with databases to reuse leverage past work or to store current work for future use. The shaded area delimited by dashes delineates stages facilitated by synthetic biology CAD software, while other stages are handled by more general purpose software. Text in blue indicates examples of software providing assisting at each stage.

Figure 2

New Instruments Connect Design and Experiment. (a) Using time-lapse microscopy for characterizing the dynamics of gene networks requires the development of custom suite of image and signal processing software along with data reduction algorithms. The mathematical models used to reduce movies into high-level statistics are necessarily related to the models used to design the gene network as ultimately experimental data need to be reconciled with model predictions. (b) Microscopy movies have traditionally been analyzed in a post-processing step. However, it is conceivable that in a near future the data analysis will be performed in real time by the computer controlling the microscope and the microfluidic system giving the user an experience similar to the use of a flow-cytometer. This information could also be used by the user to manually interact with the cells under observation. Alternatively, control algorithm could be developed to program the instrument to take specific actions such as changing the growth medium in response to specific behaviors of the cell populations.